Unit Head Anna Pedrola Biomedical Data-Software Engineers Marina Arias, Carlota Gozalbo, Mario Sánchez Image Data Engineer Cristina Villaseca Data Steward Clara Vallés
Working in close collaboration with multiple VHIO research groups, the Data Engineering for Research Unit focuses on the standardization, integration, and digitization of biomedical data. In addition to actively contributing to several research projects, the Unit develops and maintains robust infrastructure and environments that support institutional data storage, accessibility, interoperability, and governance.
The Unit manages a wide range of data types, including clinical, omics, imaging, and other biomedical datasets, aiming to maximize their usability and research value while providing investigators with appropriate tools and support. The team also contributes to the definition and implementation of Data Management Plans (DMPs), ensuring compliance with institutional and regulatory data management requirements throughout the data lifecycle.
Through the design and implementation of ETL (Extract, Transform, Load) pipelines, the development of structured and interoperable databases, the integration of heterogeneous data sources, and the creation and maintenance of specialized software solutions, the Unit provides a reliable framework that enables researchers to efficiently generate, manage, and exploit research data.
The Unit is actively advancing Artificial Intelligence (AI)-driven initiatives, including the development of clinical trial matching tools to support patient recruitment and the implementation of large language model (LLM) approaches for the structuring and extraction of information from unstructured clinical notes. These efforts aim to enhance data usability, accelerate clinical research workflows, and contribute to precision oncology initiatives.
Head of Unit Lara Nonell Bioinformaticians Irene Agustí Barea, Ángel García de la Torre García, Alba Mas Malavila, Pau Marc Muñoz Torres
VHIO’s Bioinformatics Unit (VHIOinformatics) provides research groups with cutting-edge computational resources for the analysis of cancer-related omics data. We support VHIO investigators through the implementation of state-of-the-art bioinformatic pipelines and the processing of multi-omics datasets.
Collaborating with researchers across multiple projects, we participate in different stages of research from conception or experimental design through to bioinformatic data analysis and final publication, with particular focus on visualization and functional interpretation. In 2025 we conducted fifty-eight data analyses in collaboration with twenty-five VHIO research groups. The study set comprised mainly transcriptomics and genomics data, but it was enriched by shotgun metagenomics projects to explore the tumor micro‑environment. We also performed reassessment of several publicly available datasets to gain insights into the development and spread of cancer. With the recent onboarding of single‑cell technologies and expertise, we are now analyzing several transcriptomic and multi-omics single-cell experiments.
Following the FAIR Guiding Principles for scientific data management, we have developed a guide for uploading data to public repositories, with a particular emphasis on the EGA, our reference repository for controlled-access human data. Several of our internal datasets—already featured in recent publications—have been deposited in publicly accessible repositories to support open science and data reuse.
Our computational procedures are based on open-source software developed in a secure and reproducible environment. Available to bioinformaticians in-house, and developed in collaboration with our IT department, we have continued to expand our cluster infrastructure, with the addition of a GPU partition for artificial intelligence (AI) analyses. Thanks to the Excelencia Severo Ochoa accreditation that VHIO received in 2021 as a Severo Ochoa Center of Excellence (2022-2026), and the support we receive from CRIS contra el cancer - the CRIS Cancer Foundation, we will continue to develop this infrastructure in 2026.
Our Bioinformatics Unit is a member of the Spanish translational bioinformatics network, TransBioNet, which is coordinated by the Spanish National Bioinformatics Institute (INB) and works in association with the European Life Science Infrastructure for Biological Information (ELIXIR). We also represent VHIO in various consortia and taskforces.
Unit Head Rodrigo Dienstmann Data Manager and Project Coordinator Cristina Viaplana Data Analysts Haitham Alatoom, Laura Campi, Gloria Castillo, Raquel Comas, Eduardo García, Laura González, Laia Joval, Sandra Martinez, Armando Mel, Rosa Romero, Christina Zatse
The ODysSey Group at VHIO promotes biomedical research by integrating cancer multi-omics data with clinical outcomes from oncology patients treated at the Vall d’Hebron University Hospital (HUVH). As experts in disease ontology and cancer semantics, we extract and process clinical data elements from electronic medical records. By using common data models, we standardize the format and content of observational healthcare data, harmonizing disparate coding systems with minimal information loss.
Our group designs and maintains comprehensive clinical-molecular repositories and custom data management solutions that empower researchers to conduct correlative analyses for hypothesis generation and biomarker validation, from genomics to computational pathology and radiology. Our team also assists investigators in identifying eligible patients for translational studies, clinical data collection through electronic case report forms, data processing and quality assessment. Working side by side with VHIO’s Statistics Unit, we collaborate in the design, analysis and interpretation of study results. Together with the Data Engineering for Research Unit, we deploy informatics tools to explore and visualize multi-omics data for research purposes and maintain web applications in the field of precision oncology care and clinical trial matching.
We actively participate in international real-world data analyses projects, foster collaborative research in computational oncology, and bridge connections among cancer researchers working on predictive and prognostic modeling, cancer driver identification, molecular subtyping, and tumor actionability.
Facilitate high-quality clinical-molecular correlative studies and investigator-initiated trials (IITs) at VHIO:
Promote evidence-based precision cancer care and clinical trial recruitment:
Head of Unit Guillermo Villacampa Senior Statistician Victor Navarro Statisticians Anna Aguilera, Lorenzo Carità, Julian Silan Bachelor's Student Mikhail Vlasov
VHIO’s Statistics Unit implements innovative biostatistical methodologies to optimize study design, data analysis and interpretation to enhance clinical and preclinical research. Collaborating with research groups across multiple clinical trials and observational studies, we participate in various stages of research from experimental design through to data analysis and visualization and ultimately publication. Areas of focus include sample size calculation, statistical design of clinical trials, multi-state modelling, survival analyses, cost-utility analysis, and systematic reviews and meta-analyses.
Our Unit facilitates the design and initiation of VHIO investigator-initiated studies as well as new adaptive phase I/II clinical trial designs. We work closely with researchers on the design and publication of results from various VHIO-led clinical studies as well as validating the prognostic value of new tests and cancer biomarkers. In addition, we optimize real-world data to generate new insights beyond the context of clinical trials.
Our team participates in several different European and national projects aimed at developing and implementing novel statistical designs. We also work to enhance dose-escalation study designs to optimize dose selection in oncology drug development. Furthermore, we continue to evaluate the potential of synthetic control arms to compare the effectiveness of single-arm trials.
Directed by Albert Altafaj Tardío, the Laboratory Animal Service (LAS) comprises a designated veterinary surgeon, experts specialized in rodent-colony management and experimental models, a dedicated team of preclinical imaging experts, care staff as well as technical area personnel (support and cleaning).
Laboratory rodents used for research and teaching purposes are centralized at the Laboratory Animal Service (LAS), located at CELLEX and managed by VHIO. Established in 2015, the LAS is a cutting-edge, shared facility across the Vall d'Hebron Barcelona Hospital Campus. Spanning a total surface area of 1347 m2, it has 4,347 mouse cages and 245 rat cages, and 16 equipped laboratories (202 m2).
Equipment and facilities
The LAS is divided up into seven experimental areas, as well as those dedicated to technical material-sterilization and management, administration, refrigeration storage, and type III and IV waste areas. All these areas are situated on the two underground floors, enabling experimental procedures to be conducted under strict biosafety—specific-pathogen free (SPF), conventional, non-SPF (quarantine) and biosafety level 2 (BSL2)—and microbiological conditions.
It also has a preclinical imaging platform (PIP) with rodent-dedicated optical, micro-tomographic, micro-ultrasound, histotripsy, single-photon emission computed tomography (SPECT) and positron-emission (PET CT) imaging systems.
The LAS is distributed across the following areas: